Concept: Chemical synapse
Information in a computer is quantified by the number of bits that can be stored and recovered. An important question about the brain is how much information can be stored at a synapse through synaptic plasticity, which depends on the history of probabilistic synaptic activity. The strong correlation between size and efficacy of a synapse allowed us to estimate the variability of synaptic plasticity. In an EM reconstruction of hippocampal neuropil we found single axons making two or more synaptic contacts onto the same dendrites, having shared histories of presynaptic and postsynaptic activity. The spine heads and neck diameters, but not neck lengths, of these pairs were nearly identical in size. We found that there is a minimum of 26 distinguishable synaptic strengths, corresponding to storing 4.7 bits of information at each synapse. Because of stochastic variability of synaptic activation the observed precision requires averaging activity over several minutes.
- Proceedings of the National Academy of Sciences of the United States of America
- Published over 6 years ago
A hypothesis and the experiments to test it propose that very long-term memories, such as fear conditioning, are stored as the pattern of holes in the perineuronal net (PNN), a specialized ECM that envelops mature neurons and restricts synapse formation. The 3D intertwining of PNN and synapses would be imaged by serial-section EM. Lifetimes of PNN vs. intrasynaptic components would be compared with pulse-chase (15)N labeling in mice and (14)C content in human cadaver brains. Genetically encoded indicators and antineoepitope antibodies should improve spatial and temporal resolution of the in vivo activity of proteases that locally erode PNN. Further techniques suggested include genetic KOs, better pharmacological inhibitors, and a genetically encoded snapshot reporter, which will capture the pattern of activity throughout a large ensemble of neurons at a time precisely defined by the triggering illumination, drive expression of effector genes to mark those cells, and allow selective excitation, inhibition, or ablation to test their functional importance. The snapshot reporter should enable more precise inhibition or potentiation of PNN erosion to compare with behavioral consequences. Finally, biosynthesis of PNN components and proteases would be imaged.
Bipolar disorder (BD) is a multi-factorial disorder caused by genetic and environmental influences. It has a large genetic component, with heritability estimated between 59-93%. Recent genome-wide association studies (GWAS) using large BD patient populations have identified a number of genes with strong statistical evidence for association with susceptibility for BD. Among the most significant and replicated genes is ankyrin 3 (ANK3), a large gene that encodes multiple isoforms of the ankyrin G protein. This article reviews the current evidence for genetic association of ANK3 with BD, followed by a comprehensive overview of the known biology of the ankyrin G protein, focusing on its neural functions and their potential relevance to BD. Ankyrin G is a scaffold protein that is known to have many essential functions in the brain, although the mechanism by which it contributes to BD is unknown. These functions include organizational roles for subcellular domains in neurons including the axon initial segment and nodes of Ranvier, through which ankyrin G orchestrates the localization of key ion channels and GABAergic presynaptic terminals, as well as creating a diffusion barrier that limits transport into the axon and helps define axo-dendritic polarity. Ankyrin G is postulated to have similar structural and organizational roles at synaptic terminals. Finally, ankyrin G is implicated in both neurogenesis and neuroprotection. ANK3 and other BD risk genes participate in some of the same biological pathways and neural processes that highlight several mechanisms by which they may contribute to BD pathophysiology. Biological investigation in cellular and animal model systems will be critical for elucidating the mechanism through which ANK3 confers risk of BD. This knowledge is expected to lead to a better understanding of the brain abnormalities contributing to BD symptoms, and to potentially identify new targets for treatment and intervention approaches.
Cholinergic neuromodulation plays key roles in the regulation of neuronal excitability, network activity, arousal, and behavior. On longer time scales, cholinergic systems play essential roles in cortical development, maturation, and plasticity. Presumably, these processes are associated with substantial synaptic remodeling, yet to date, long-term relationships between cholinergic tone and synaptic remodeling remain largely unknown. Here we used automated microscopy combined with multielectrode array recordings to study long-term relationships between cholinergic tone, excitatory synapse remodeling, and network activity characteristics in networks of cortical neurons grown on multielectrode array substrates. Experimental elevations of cholinergic tone led to the abrupt suppression of episodic synchronous bursting activity (but not of general activity), followed by a gradual growth of excitatory synapses over hours. Subsequent blockage of cholinergic receptors led to an immediate restoration of synchronous bursting and the gradual reversal of synaptic growth. Neither synaptic growth nor downsizing was governed by multiplicative scaling rules. Instead, these occurred in a subset of synapses, irrespective of initial synaptic size. Synaptic growth seemed to depend on intrinsic network activity, but not on the degree to which bursting was suppressed. Intriguingly, sustained elevations of cholinergic tone were associated with a gradual recovery of synchronous bursting but not with a reversal of synaptic growth. These findings show that cholinergic tone can strongly affect synaptic remodeling and synchronous bursting activity, but do not support a strict coupling between the two. Finally, the reemergence of synchronous bursting in the presence of elevated cholinergic tone indicates that the capacity of cholinergic neuromodulation to indefinitely suppress synchronous bursting might be inherently limited.
The proteome of human brain synapses is highly complex and is mutated in over 130 diseases. This complexity arose from two whole-genome duplications early in the vertebrate lineage. Zebrafish are used in modelling human diseases; however, its synapse proteome is uncharacterized, and whether the teleost-specific genome duplication (TSGD) influenced complexity is unknown. We report the characterization of the proteomes and ultrastructure of central synapses in zebrafish and analyse the importance of the TSGD. While the TSGD increases overall synapse proteome complexity, the postsynaptic density (PSD) proteome of zebrafish has lower complexity than mammals. A highly conserved set of ∼1,000 proteins is shared across vertebrates. PSD ultrastructural features are also conserved. Lineage-specific proteome differences indicate that vertebrate species evolved distinct synapse types and functions. The data sets are a resource for a wide range of studies and have important implications for the use of zebrafish in modelling human synaptic diseases.
Alpha-synuclein is known to bind to small unilamellar vesicles (SUVs) via its N terminus, which forms an amphipathic alpha-helix upon membrane interaction. Here we show that calcium binds to the C terminus of alpha-synuclein, therewith increasing its lipid-binding capacity. Using CEST-NMR, we reveal that alpha-synuclein interacts with isolated synaptic vesicles with two regions, the N terminus, already known from studies on SUVs, and additionally via its C terminus, which is regulated by the binding of calcium. Indeed, dSTORM on synaptosomes shows that calcium mediates the localization of alpha-synuclein at the pre-synaptic terminal, and an imbalance in calcium or alpha-synuclein can cause synaptic vesicle clustering, as seen ex vivo and in vitro. This study provides a new view on the binding of alpha-synuclein to synaptic vesicles, which might also affect our understanding of synucleinopathies.
The search for new “neuromorphic computing” architectures that mimic the brain’s approach to simultaneous processing and storage of information is intense. Because, in real brains, neuronal synapses outnumber neurons by many orders of magnitude, the realization of hardware devices mimicking the functionality of a synapse is a first and essential step in such a search. We report the development of such a hardware synapse, implemented entirely in the optical domain via a photonic integrated-circuit approach. Using purely optical means brings the benefits of ultrafast operation speed, virtually unlimited bandwidth, and no electrical interconnect power losses. Our synapse uses phase-change materials combined with integrated silicon nitride waveguides. Crucially, we can randomly set the synaptic weight simply by varying the number of optical pulses sent down the waveguide, delivering an incredibly simple yet powerful approach that heralds systems with a continuously variable synaptic plasticity resembling the true analog nature of biological synapses.
Although ubiquitin ligases have been implicated in autism, their roles and mechanisms in brain development remain incompletely understood. Here, we report that in vivo knockdown or conditional knockout of the autism-linked ubiquitin ligase RNF8 or associated ubiquitin-conjugating enzyme UBC13 in rodent cerebellar granule neurons robustly increases the number of parallel fiber presynaptic boutons and functional parallel fiber/Purkinje cell synapses. In contrast to the role of nuclear RNF8 in proliferating cells, RNF8 operates in the cytoplasm in neurons to suppress synapse differentiation in vivo. Proteomics analyses reveal that neuronal RNF8 interacts with the HECT domain protein HERC2 and scaffold protein NEURL4, and knockdown of HERC2 or NEURL4 phenocopies the inhibition of RNF8/UBC13 signaling on synapse differentiation. In behavior analyses, granule neuron-specific knockout of RNF8 or UBC13 impairs cerebellar-dependent learning. Our study defines RNF8 and UBC13 as components of a novel cytoplasmic ubiquitin-signaling network that suppresses synapse formation in the brain.
It is assumed that synaptic strengthening and weakening balance throughout learning to avoid runaway potentiation and memory interference. However, energetic and informational considerations suggest that potentiation should occur primarily during wake, when animals learn, and depression should occur during sleep. We measured 6920 synapses in mouse motor and sensory cortices using three-dimensional electron microscopy. The axon-spine interface (ASI) decreased ~18% after sleep compared with wake. This decrease was proportional to ASI size, which is indicative of scaling. Scaling was selective, sparing synapses that were large and lacked recycling endosomes. Similar scaling occurred for spine head volume, suggesting a distinction between weaker, more plastic synapses (~80%) and stronger, more stable synapses. These results support the hypothesis that a core function of sleep is to renormalize overall synaptic strength increased by wake.
Understanding the computations that take place in brain circuits requires identifying how neurons in those circuits are connected to one another. We describe a technique called TRACT (TRAnsneuronal Control of Transcription) based on ligand-induced intramembrane proteolysis to reveal monosynaptic connections arising from genetically labeled neurons of interest. In this strategy, neurons expressing an artificial ligand (‘donor’ neurons) bind to and activate a genetically-engineered artificial receptor on their synaptic partners (‘receiver’ neurons). Upon ligand-receptor binding at synapses the receptor is cleaved in its transmembrane domain and releases a protein fragment that activates transcription in the synaptic partners. Using TRACT in Drosophila we have confirmed the connectivity between olfactory receptor neurons and their postsynaptic targets, and have discovered potential new connections between neurons in the circadian circuit. Our results demonstrate that the TRACT method can be used to investigate the connectivity of neuronal circuits in the brain.